{"title":"The asymmetric impact of Twitter Sentiment and emotions: Impulse response analysis on European tourism firms using micro-data","authors":"Efstathios Polyzos , Anestis Fotiadis , Tzung-Cheng Huan","doi":"10.1016/j.tourman.2024.104909","DOIUrl":null,"url":null,"abstract":"<div><p>This paper examines the characteristics that drive conflicting outcomes on the impact of Twitter data on firm returns using financial micro data. Using 314 European tourism firms as a case study and a sample of 63 million Tweets, we build sentiment and emotion (anger, fear, joy) data series and use them to compute impulse response functions for firm returns. Our results indicate that firm size and popularity are the most important firm features that explain the asymmetric impact of Twitter sentiment and of the anger emotion, while debt explains the variations in the impact of the fear emotion. We also find that the impact of the joy emotion is more evident before the COVID-19 pandemic and more muted after the outbreak. Our findings reconcile varied research on Twitter's impact on tourism industry returns and provide insights to practitioners on using Twitter to gauge online users' collective knowledge of real outcomes.</p></div>","PeriodicalId":48469,"journal":{"name":"Tourism Management","volume":null,"pages":null},"PeriodicalIF":10.9000,"publicationDate":"2024-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Tourism Management","FirstCategoryId":"91","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0261517724000281","RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENVIRONMENTAL STUDIES","Score":null,"Total":0}
引用次数: 0
Abstract
This paper examines the characteristics that drive conflicting outcomes on the impact of Twitter data on firm returns using financial micro data. Using 314 European tourism firms as a case study and a sample of 63 million Tweets, we build sentiment and emotion (anger, fear, joy) data series and use them to compute impulse response functions for firm returns. Our results indicate that firm size and popularity are the most important firm features that explain the asymmetric impact of Twitter sentiment and of the anger emotion, while debt explains the variations in the impact of the fear emotion. We also find that the impact of the joy emotion is more evident before the COVID-19 pandemic and more muted after the outbreak. Our findings reconcile varied research on Twitter's impact on tourism industry returns and provide insights to practitioners on using Twitter to gauge online users' collective knowledge of real outcomes.
期刊介绍：
Tourism Management, the preeminent scholarly journal, concentrates on the comprehensive management aspects, encompassing planning and policy, within the realm of travel and tourism. Adopting an interdisciplinary perspective, the journal delves into international, national, and regional tourism, addressing various management challenges. Its content mirrors this integrative approach, featuring primary research articles, progress in tourism research, case studies, research notes, discussions on current issues, and book reviews. Emphasizing scholarly rigor, all published papers are expected to contribute to theoretical and/or methodological advancements while offering specific insights relevant to tourism management and policy.
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
